tbuckley/cabot-search huggingface dataset:
Predicting which cancer patients will see a psychiatrist or counsellor from their initial oncology consultation document using natural language processing.
Authors: John-Jose Nunez, Bonnie Leung, Cheryl Ho, Raymond T. Ng, Alan Bates
Journal: Journal of Clinical Oncology (2023)

e13544 Background: Patients with cancer often have unmet psychosocial needs. Early detection of who might require referral to a counsellor or psychiatrist may help improve their care. In this work, we investigated whether natural language processing (NLP) can predict which patients will see a counsellor or psychiatrist from a patient’s initial oncologist consultation document. NLP is the branch of artificial intelligence that uses language models to accomplish tasks using written text. A different application of NLP has recently been popularized through the ChatGPT online question-answering system. In this work, we used traditional and neural language models to predict whether patients will see a psychiatrist or counsellor based on their initial oncologist consultation document. Methods: This retrospective prognostic study used data from 47,625 of 59,800 patients who received initial cancer care at any of the 6 BC Cancer sites located in the province of British Columbia between April 1, 2011 and December 31, 2016. We excluded patients with multiple cancer diagnoses, or those that did not see a medical or radiation oncologist within 180 days of their cancer diagnosis. We trained neural language models to predict which patients would see a psychiatrist or counsellor in the twelve months following their initial oncologist consultation. We used the non-neural language model bag-of-words, as well as three neural models: convolutional neural networks (CNN), long-short term memory, and bidirectional encoder representations from transformers. Results: The models performed similar to or better than previous applications of artificial intelligence in predicting psychosocial needs. Our best-performing models, utilizing CNNs, achieved a balanced accuracy above 75% and a receiver-operator area-under-curve (AUC) above 0.80 when predicting which patients would see a psychiatrist. Performance was lower for predicting which patients would see a counsellor, with balanced accuracy and AUC exceeding 70% and 0.75, respectively. We examined what words or phrases our models used to make the predictions, finding symptom burden, certain cancers, and family history of cancer were positive predictors of future referral to psychosocial services. Conclusions: Our results suggest NLP can be used to predict which cancer patients require referral to a psychiatrist or counsellor from their initial oncologist consultation. Future research may be able to extend our work to predict other needs of cancer patients such as palliative care, or other cancer outcomes more generally.
Identification of clinically actionable biomarkers in an Indian cancer cohort using comprehensive genomic profiling (CGP): An institutional experience.
Authors: Mithua Ghosh, Gautam Balaram, Sheela ML, Krishna CR, Shekar Patil, Sridhar PS, Satheesh Chiradoni Thungappa, Somarat Bhattacharjee, Ramya Kodandapani, Vijay K, Vijay E, Suhas N. Ghorpade, Roshini Dasgupta, Mohammed Naseer, Shanmukh Katragadda, Aarthi Ravichandran, Veena Ramaswamy, Srinivasa Bj, Vishal Uchila Shishir Rao, Basavalinga Sadasivaiah Ajaikumar
Journal: Journal of Clinical Oncology (2023)

e15166 Background: CGP through Next-Generation Sequencing (NGS) has substituted single-gene testing to identify more druggable gene aberrations. The simultaneous detection of broad spectrum predictive biomarkers and molecular signatures including tumor mutational burden (TMB), microsatellite instability (MSI) burden, somatic BRCA, homologous recombination repair genes (HRR) and RNA variants by CGP provides a more cost efficient and tissue-preserving approach than serial single-biomarker analyses. Methods: 750 biopsy proven patients of various cancer spectrum at HCG cancer center were consented and profiled using Illumina TruSight Oncology 500 (TSO500) assay that interrogates 523 cancer-related genes on NextSeq in an IRB-approved prospective study. The findings were discussed in molecular tumor board (MTB) and recommendations from treating physicians were documented in patient records for change in clinical management and follow up. Results: A total of 1291 genomic alterations were detected in 750 cases (mean 1.7 mutations/sample). CGP identified genetic alterations with therapeutic and prognostic implications in 77% patients (Tier I- 34%, Tier II-64%, Tier III-14%). CGP revealed higher number of druggable genes (47%) than small panels (14%).Tumor agnostic markers for immunotherapy (IO) were observed in 20% of the current cohort, based on which IO was initiated and are on follow up. In 20% of the cohort, HRR pathway alterations including s BRCA (7%) were detected providing an option to treat with platinum or PARP inhibitors. Other significant alterations like EGFR, RAS/RAF, ERBB2, PIK3CA, cKIT, PDGFRA, ARID1A, ARID2, POLE, and FGFR were found. RNA sequencing yielded 54 RNA alterations (38 translocations and 16 splice variants). Androgen receptor splice variants were observed in 50% prostate carcinoma patients for whom taxane therapy was initiated. Other frequent fusions detected were: TMPRSS-ERG, RPS6KB1-VMP1, EML4-ALK, NTRK, PDGFRA and EWSR. Conclusions: CGP reports actionable and prognostic genetic alterations in 77% of patients who could potentially benefit by tumor-matched targeted and immunotherapy. Post MDT patients were assigned to approved therapies (5-80%) or change in clinical management (5-25%) based on the cancer type (Table). 25% patients were enrolled for investigator initiated clinical trials and are on follow up for clinical outcome and analysis of independent prognostic and therapeutic value of novel biomarkers in a larger cohort of Indian patient. [Table: see text]
Reveal irAE by analysis of 197,921 claim-based prescriptions.
Authors: Jeremiah Gordon Scholl, An Jim Long, Yu-Chuan (Jack) Li
Journal: Journal of Clinical Oncology (2023)

e13639 Background: immune-related adverse effects (irAE) are widely known for immune checkpoint inhibitors (ICI), but medications used to relieve irAE based on patient profile and condition are not offered in guidelines. Publications are available to reveal irAE from hospitals, but the number of cases are normally only a few hundred and insufficient to stratify by more variables. Claim-based data points were also used in a few publications, based on analysis of diagnosis code such as ICD-9 and ICD-10. However, missing or wrong coding of adverse effects are well-known and over-exaggerated for severe adverse events, and are also affected by reimbursement policy. This research used medications from a large national health system to understand irAE and treatments related to them. Methods: 2017-2019 National Health Insurance database (NHIDB) in Taiwan was used. The case group was identified as (2,474) patients who used PD-1 inhibitors (more specifically Nivolumab, Pembrolizumab, and Atezolizumab because only those three were available in the duration). A control group was identified as (6,207) patients given platinum-based chemotherapy (cases using other cancer drugs at the same time were excluded). Odds ratios were calculated to see frequency of irAE and medications in both groups. Results: Top 10 medications are listed. Diphenhydramine and pain killers were the most common AE-relief medications for cancer patients in NHIDB and only anilides (mostly propacetamol) are overlapped. The rest of the drugs with OR &gt; 3, especially steroids (thyroid and corticosteroids), were used mainly for irAE. Conclusions: The research reveals a novel approach to understand how physicians prescribe to treat irAE. The larger number of cases reported compared to previous studies suggests that such a database can be used for future research, including to reveal demographic patterns, and to aid the development of guidelines, teaching aids, and decision support.[Table: see text]
Telemedicine and cancer care in Syria: A promising initiative during the war and COVID-19 era.
Authors: Maher Saifo, Mousa Alali
Journal: Journal of Clinical Oncology (2023)

e13680 Background: Telemedicine (TM) is the practice of medicine using technology to deliver care to patients at their locations. One of the major difficulties that cancer patients in Syria face is the ability to frequently visit Albairouni University Cancer Center (ABUH) in Damascus. The travel-related barriers to reach ABUH have increased due to the war, unsafe road, shortage of fuel, and high travel costs. Moreover, in response to the COVID-19 pandemic in the country, healthcare providers reduced unnecessary visits. Here, we present an initiative illustrating our Syrian experience of TM in cancer care. Methods: The initiative began on 2 January 2021 to serve cancer patients near to Salamyieh (a rural area, 3-hour drive to ABUH). We satellite a clinic located near to patients’ homes, and we provide it with the necessary telecommunication infrastructure to virtually contact me at ABUH. The team, consisting of physicians and volunteers, meet patients and help me gather the history, symptoms and all relevant documents to set up and complete the care plan. Patients who need to receive treatment present to ABUH where the cancer therapies are completely free of charge. The whole services of this initiative are free including the E-consults, follow-ups, and auto transportation back and forth to ABUH. The volunteers accompany and help patients in their trips to AHBU, as many of them lost their beloved caregivers due to the war. Results: Throughout the last 2 years, we served 500 new patients. The numbers of E-consults were 920 and 800 in 2021 and 2022, respectively. Few patients were uncomfortable with it due to the lack of in-person interaction. Thus, it was a challenge to build connection and trust with patients virtually. Conclusions: Collectively, despite of the limited resources, TM initiatives have a lot to offer for patients with cancer and present a great solution to follow up with them. This experience shows that TM works especially in low-income countries, during the pandemic, and in a war-affected setting, all of which are associated with poor socioeconomic status and insecurity.
Hospital Anxiety and Depression Scale (HADS) score trends among testicular cancer survivors: A longitudinal study.
Authors: Khalid Y. Alkhatib, Daniel Roberson, Ruchika Talwar, Hanna Jia, Katherine Nathanson, S. Bruce Malkowicz, Thomas J. Guzzo, Phillip Pierorazio, Linda A. Jacobs, David J. Vaughn
Journal: Journal of Clinical Oncology (2023)

5042 Background: The rarity of testicular germ cell tumors, in conjunction with the young age of its patients, makes it challenging to study its long-term adverse effects. We sought to investigate the changes in Hospital Anxiety and Depression Scale (HADS) scores over time in our institutional cohort of testicular cancer (TC) survivors, hypothesizing that anxiety and depression indices will improve over time, and specifically after treatment completion. Methods: A longitudinal analysis of TC survivors at the University of Pennsylvania between 2013 and 2020, quality of life metrics were measured annually during routine clinic visits. A validated HADS score was utilized to calculate indices of anxiety and depression. Multivariable linear mixed-effects regression models adjusted for pathology type, stage, treatment type, age, marital status, education, income, insurance, employment status, living situation, and time from diagnosis to first survey administration were used to calculate the mean predicted HADS, HADS-Anxiety, and HADS-Depression scores. ANOVA was used to test for parallelism and changes between survey scores. Each item is rated on a 4-point scale (ranging from 0 = no not at all, to 3 = yes definitely), for a total score ranging from 0-21 for each sub-scale with a cut-off point of 8/21 for anxiety or depression. Results: A total of 353 patients were included in the study. Baseline mean scores were 7.3, 4.9, and 2.4 for HADS overall, HADS-Anxiety, and HADS-Depression, respectively. Mean scores did not change over time, ANOVA testing of p=0.84, p=0.78, and p=0.0.65 for overall HADS, HADS-Anxiety, and HADS-Depression, respectively. Stratification by pathology, stage, or treatment did not show any significant interaction. Conclusions: Our data demonstrates that there was no significant change over time in HADS scores, thus considering the risks associated with depression and anxiety, such as suicide, it is essential to consider early referrals to psychiatric services. Our results are from a single institution, limited by a small sample size, and data lacks granularity, including mental health history. Nonetheless, our findings serve as a framework for future prospective studies of TC survivors.
Gene expression-based machine learning approach to predict immunotherapy response and survival in patients with advanced cancer.
Authors: Zheng Zhang, Xianyun Wang, Qi Tang, Kaiwei Yang, Xuanjun Guo, Aixiang Wang, Yiqun Zhang, Yantong Hao, Zhihua Pei, Dongliang Wang, Qiming Zhou, Zhisong He
Journal: Journal of Clinical Oncology (2023)

1550 Background: Immune checkpoint blockades (ICBs) have drastically improved the clinical outcomes of cancer patients, while only ~30% of them get significant benefits from immunotherapy. TMB, PD-L1, TNB, GEP (Cristescu et al. 2018) and other conventional biomarkers can explain only ~60% of the ICB response, suggesting that novel factors are yet to be discovered. Methods: Gene expression profiles and clinical information of 672 patients were collected from IMvigor210 (n=348, bladder cancer), Pender et al. (n=98, 20 tumor types), Kim et al. (n=45, gastric cancer) and CheckMate (n=181, kidney cancer) cohorts, in which all patients were treated with ICBs. In each sample, gene expression intensities normalized by RPKM were ranked in descender order (range of 1-20000) and scaled into the 0-1 range lastly. To identify immune signatures that correlated with both response and survival, 1000+ immune genes were downloaded from InnatDB database, and their expression values were compared between the two groups of IMvigor210 data which were divided according to response (CR+PR vs. SD+PD, Wilcoxon test) or overall survival (≥mOS vs. ＜mOS, Cox survival analysis). Bayesian-regularization neural networks (BRNN) model was used to develop the risk model to predict ICB response and prognosis. 75% of IMvigor210 data were randomly selected as the training set, and the remaining 25% as the test set. The performance of predictor was independently validated in Pender et al., Kim et al., and CheckMate cohorts subsequently. ROC curves were used to evaluate the predictive accuracy to response. Survival plots were created using the Kaplan-Meier estimator, and data were analyzed by log-rank test. Results: 40 DEGs (including top20 DEGs positively correlated with ORR/OS and top20 DEGs negatively correlated with ORR/OS) were identified as immune signatures, in which each gene signature could significantly distinguish ICB response and survival. Our model outperformed TMB or GEP in the prediction of response in IMvigor210 (Model = 0.986 vs. TMB = 0.728 vs. GEP = 0.551), Pender et al. (Model = 0.757 vs. TMB = 0.593 vs. GEP = 0.621), Kim et al. (Model = 0.881 vs. GEP = 0.828), and CheckMate (Model = 0.927 vs. TMB = 0.543) cohorts when AUC was used as performance metric. Meanwhile, our model showed promising results for differentiating longer survivors from shorter survivors with p vale ＜0.0001, 0.064, 0.021, and 0.0006 in IMvigor210, Pender et al., Kim et al., and CheckMate cohorts respectively. Conclusions: We proposed a deep learning model to predict ICB response and survival, in which feature selection based on immune gene expression order, allowing all kinds of platforms and expression data types. Our model showed a robust prediction not only in bladder cancer, but also in other pan-cancer types.
Outcome of second-line treatment after CDK4/6 inhibitors in hormonal-positive HER-2 negative metastatic breast cancer: Single institution experience.
Authors: Hosam Alghanmi, Shereef Ahmed Elsamany, Khaled Elnaghi
Journal: Journal of Clinical Oncology (2023)

e13053 Background: In patients with metastatic hormonal receptors (HR)-positive, HER2-negative breast cancer, CDK 4/6 inhibitors with hormonal therapy is the current standard first line therapy in patients without visceral crisis. Limited data is available about the outcome of second line therapy after CDK 4/6 inhibitors. In this study, we reported the survival outcome of second line systemic therapy after CDK 4/6 inhibitors in a single institute in Saudi Arabia. Methods: We retrospectively checked patients with metastatic HR-positive, HER2-negative breast cancer who received first line therapy with palbociclib in addition to an aromatase inhibitor in King Abdullah Medical City, Saudi Arabia. Patients who received second line systemic therapy were recruited. Different clinicopathological data were checked in addition to type of second line therapy, dates of starting 1 st and second lines therapy and dates of progression. We check progression-free survival (PFS) with second line therapy in relation to the type of second line therapy, duration of 1 st line therapy and other potential prognostic factors. Results: We recruited 59 eligible patients. Median PFS of the study group was 4 months (95% CI 2.9-5.1). No significant difference in PFS according to type of second line systemic therapy (chemotherapy: 4 months, everolimus with hormonal therapy: 6 months, hormonal monotherapy: 3 months, p=0.17). In addition, there was no significance difference in second line therapy PFS according to duration of 1 st line palbociclib-hormonal therapy (≤ 12 months: 4 months vs. &gt;12 months: 5 months, HR 0.97, 95% CI: 0.55-1.7, p=0.92). Similarly, taking 6 months as a cutoff, no significant difference in PFS (≤ 6 months: 4 months, &gt;6 months: 6 months, HR 0.73, 95% CI: 0.43-1.24, p=0.25). Similarly, no difference in second line PFS according to menopausal status, age at diagnosis (≤ 50 vs &gt;50) or ER-Allred score (≤ 6 vs &gt;6). Conclusions: Outcome of 2 nd line systemic therapy following first line palbociclib with hormonal therapy was poor in the study cohort. No significant difference in PFS according to type of systemic therapy, duration of first line therapy, or other clinicopathological factors.
Osmotic blood-brain barrier disruption with mannitol followed by methotrexate, rituximab, and carboplatin in treating patients with newly diagnosed primary central nervous system lymphoma.
Authors: Prakash Ambady, Nancy Diane Doolittle, Edward A. Neuwelt, Rongwei (Rochelle) Fu, Gerda Teglassy, Anh Huan Vo
Journal: Journal of Clinical Oncology (2023)

2077 Background: Osmotic blood-brain barrier disruption (BBBD) uses intra-arterial (IA) mannitol to open the neuro-vascular unit to enhance delivery of therapeutic agents to the brain. We report the results of a multi-institutional, single arm, phase 2 study evaluating the efficacy and safety of BBBD-enhanced chemotherapy in combination with immunotherapy in patients with newly diagnosed primary central nervous system lymphoma (PCNSL). PCNSL is a rare non-Hodgkin’s lymphoma that is limited to the brain, cerebrospinal fluid, spinal cord and/or the vitreoretinal compartment. Methods: Non-immunocompromised subjects with newly diagnosed PCNSL received rituximab IV over 5 hours on day 1. On days 2 and 3, under general anesthesia in the angiography suite, subjects received IA mannitol immediately followed by IA methotrexate over 10 minutes, and then IA carboplatin over 10 minutes. Subjects received sodium thiosulfate IV for hearing protection at 4 and 8 hours after each carboplatin dose. Treatment was repeated every month for up to 12 courses in the absence of disease progression or unacceptable toxicity. Per institutional recommendations, further accrual was terminated during the COVID-19 pandemic. Contrast MRI was used for response assessment based on IPCG criteria. Results: Twenty subjects (10 F, 10 M, Median KPS = 80; range 40-100) received a median of 8 cycles at 3 US institutions. Sixteen radiographic complete responses (80%) and 1 partial response were documented, 3 subjects were not evaluable (2 withdrew consent and 1 unrelated death). Median PFS was 55.2 months (95% CI :10.3 – not reached) and Median Overall survival was 82.8 months (95% CI :19.8-145.8). Fourteen patients (82% of evaluable patients) had grade 3 or 4 adverse events (AE). Grade 4 AEs (n = 14 in n = 7 patients) included neurologic toxicities (ischemia, cervical cord inflammation, neuropathy) and blood/bone marrow toxicities (lymphopenia, neutropenia, granulocytopenia). There were no treatment-related deaths. Conclusions: We demonstrate the feasibility of performing BBBD in a multi-institutional setting with excellent PFS and OS in patients without whole brain radiation or autologous transplant. Our CR rates, PFS and OS are comparable to other IV high-dose MTX regimens, with acceptable toxicity profile and no documented treatment-related deaths. Clinical trial information: NCT00293475 .
Dose rounding bevacizumab and its biosimilars to reduce drug waste in the oncology care model in a community oncology network.
Authors: Puneeth Indurlal, Naiyar Alam, Jody S. Garey, Lalan S. Wilfong
Journal: Journal of Clinical Oncology (2023)

1529 Background: The Oncology Care Model (OCM) was a 6-year long Medicare value-based care (VBC) program that rewarded practices for decreasing TCOC compared to a benchmark price, while maintaining high-quality cancer care. Drug waste from partially used single dose vials (SDV) of expensive anti-neoplastic agents is a leading contributor to avoidable Total Cost of Care (TCOC) expenditures for payers. Dose rounding (DR) of biological anti-neoplastic agents, using recommendations (https://www.nccn.org/docs/default-source/clinical/order-templates/hopa.pdf?sfvrsn=3af91118_6) from the Hematology Oncology Pharmacists Association (HOPA) and endorsed by the National Comprehensive Cancer Network (NCCN), is a standard approach to mitigate the impact of drug waste. Many of the practices in The US Oncology Network (The Network) adopted a DR program for biologic agents in 2018 as a strategy to reduce drug waste and TCOC. We studied the impact of a DR initiative targeting bevacizumab and its biosimilars (B+B) on TCOC and drug waste expenditures for The Network practices participating in the OCM. Methods: Claims data for 14 practices in The Network participating in the OCM were assessed. Drug administration data for B+B was used to evaluate drug waste, total dose, TCOC, DR and the financial impact of drug waste reduction on TCOC from 2017 to 2021. Results: In 2017, prior to implementing DR, an average of 5.3% (range 4.6% to 5.5%) of the total dose of B+B was wasted, with ~25% of B+B administrations having waste in excess of 10% of the total dose. Implementation of the initiative led to a reduction of waste on 30% of the total administrations of B+B across 14 OCM participant practices in The Network. As a result of DR, B+B drug waste decreased by 55% to an average of 2.5% (range - 2.3% to 2.7%) of the total dose in 2021. Decreasing drug waste resulted in TCOC reduction of approximately $100 per member episode per month (0.97% of TCOC) for episodes with B+B administrations in the OCM. The highest waste reduction was seen with B+B administered for treatment of gastrointestinal cancers (colon, rectal, anal, gastroesophageal, or pancreatic cancers) compared to other cancer types (lung, brain, ovarian, etc.), and for B+B administrations where drug waste was greater than 10% of the total dose (~50% reduction). Conclusions: Drug waste contributes avoidable expenditures to the TCOC. Implementing strategies such as DR can offset the impact of drug waste and offer meaningful TCOC savings for VBC programs such as the OCM. A similar DR approach may be adopted for other high-cost biologic agents where drug waste results from partial use of SDVs.